Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,200
datasets available to search
ShareScore release 0.9.0
Dataset results
3,200 results for “indexicality”
Annual seasonality trends of Enhanced Vegetation Index (EVI), Maricopa County, Arizona, 2001-2018
Description: A dataset with 18 years (2001-2018) of consistent, spatial and temporal patterns of enhanced vegetation index (EVI) values in Maricopa County AZ Abstract: This dataset consists of 18 years (2001-2018) of consistent, spatial, and temporal patterns of vegetation indices, as expressed by the enhanced vegetation index (EVI), in Maricopa County, AZ. I download and process images, at 250m resolution, from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS uses the atmospherically-corrected reflectance in the red, near-infrared, and blue wavebands to calculate vegetation indices. In the last decades, vegetation indices have been widely used for monitoring the seasonal variation of vegetation, document vegetation structure, productivity, overall health, and land cover changes and measure vegetation productivity in desert landscapes. EVI is also of high interest to investigate the potential distribution of plant and animal species and to investigate the effect of climate change on vegetation productivity. MODIS data were obtained from https://lpdaac.usgs.gov, maintained by the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC) at the USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota. Spatial Extent: Maricopa County, AZ, USA.
Minneapolis-St. Paul, MN Canopy Temperature and Combined Urban Tree Index (CUTI), 2018-2021
This dataset includes a series of raster datasets of canopy temperature across Minneapolis-St. Paul, MN at a resolution of approximately 70 meters. There are data from five different warm, summer afternoons from 2018-2021. The canopy temperature data was derived from ECOSTRESS Land Surface Temperature and Emissivity data and high-resolution land cover data using a downscaling approach. Canopy temperature acts as a proxy of canopy health and function, with higher temperatures indicative of higher stress and lower function in the canopy. For each image, we also compute the combined urban tree index (CUTI), a metric we developed that provides an indication of relative benefits from urban canopy which arise from a combination of the amount and function/health of urban canopy (based on the canopy temperature). CUTI ranges from 0-1, with high values indicating areas likely experiencing greater canopy benefits due to greater canopy cover and better canopy health/function.
Tree seedling germination, precipitation index, and SWE data for subalpine forest, 1940-2010
Annual germination dates for over 450 Engelmann spruce and over 500 subalpine fir seedlings collected across a complex topographic-moisture gradient were compared to climate variability in the Colorado Front Range. This dataset contains the SPEI (standardized-evaporation precipitation index) and snow-water equivalent (SWE) data from 1940 to 2010 used in the study as well as the number of seedlings establishing each year from 1940 to 2010 by species.
Normalized difference vegetation index data for Saddle snowfence, 1994.
A snowfence was built in 1993 on the Niwot Ridge Saddle grid to determine the effects of changes in snowpack on a number of variables, one of which was vegetation greenness (measured through the normalized difference vegetation index). The study area of the snowfence was 60m x 125m. Spectral data in the red and near infra- red bands were recorded at sixty plots (points) in four rows located approximately at 10, 25, 45, and 75 meters east of the fence (the drift area). The plots were marked with thin wire stakes put into the ground and flagged (for visibility) and given aluminum tags with their plot identification code. All the plots were located in Kobresia myosuroides communities. In each row there were ten plots located in control areas just to the north and south of the area affected by the snowfence -- five to the north and five to the south -- and five plots located in the drift area of the snowfence. The individual plots were broken into groups of five according to their location (i.e., their distance from the fence (row), and location within their row (north, south, or within the snowfence area)). Within each of these groups, the plots were given a number starting with one and going to five. The plots were then given unique codes made up of plot type (c for control and sf for snowfence), location within a row (for the control plots only - n for north and s for south), the distance in meters of the row from the snowfence (10, 25, 45, or 75), and the number that uniquely identifies each plot within a group (one through five). For example, the code cn10_1 represents plot number one of the group of control plots north of the snowfence and 10 meters east of the snowfence. The location of each plot was measured as set of coordinates within the snowfence area. The southern terminus of the snowfence was used as the origin, with the y-axis running along the snowfence and the x-axis running perpendicular to the snowfence at it's southern end. The first coordinate was t
Gini index mean score grain size estimates for Murray formation rocks (Gale crater, Mars) from ChemCam LIBS data (sols 766-1804)
<p>This repository includes main research results from the Journal of Geophysical Research: Planets manuscript entitled <em>"Grain Size Variations in the Murray Formation: Stratigraphic Evidence for Changing Depositional Environments in Gale Crater, Mars"</em>. These datasets were also included as Supplementary tables with the manuscript. Please find the plain language summary of the manuscript and the captions for these datasets below:</p> <p><strong><em>Plain language summary:</em></strong> The lowest exposed rocks of the Murray formation in Gale crater, Mars are interpreted as ancient lake deposits based on <em>Curiosity </em>rover data. However, the duration and temporal variability of this ancient lake is still an open question. Here we characterize the vertical distribution of deposits within the entire Murray formation using new grain size information. Characterizing grain size in rocks provides information about the speed of past fluid flows, which is crucial for interpreting depositional environments. However, measuring grain size in images is rarely possible for martian rocks. Thus, we estimate grain sizes with the Gini Index Mean Score (GIMS), a grain-size proxy that uses ChemCam Laser Induced Breakdown Spectroscopy data. GIMS results indicate that the Murray formation is dominated by rocks with mud-sized grains (i.e., mudstones), suggesting mud-sized grain settled in a low energy lake environment. Mud cracks occur in some of the mudstones, indicating drying periods in a lake. Rocks with sand-sized grains (i.e., sandstones) and cross bedding occur at specific intervals, suggesting episodes with stream channels and wind-blown sand dunes. The dominance of lake deposits interspersed with stream deposits suggests that liquid water was present in Gale crater for tens of thousands to millions of years.</p> <p><strong>Table captions:</strong></p> <p><em>Table S3. </em>All Murray formation targets used in the Gini mean index score (GIMS) analysis (sols 766-1804) with summary information, general grain size estimates from MAHLI and RMI images if known, and G<sub>MEAN </sub>values with associated standard deviation errors. For targets with N/A grain sizes, grains could not be resolved in any of the images, or images were not available. Protrusions in the rocks that are not grains are likely diagenetic nodules or concretions. Targets with G<sub>MEAN</sub>=0.07 have transitional GSRs, indicated by GSR1/GSR2. Targets names are merged in the same cell for those analyses that were taken on the same rock exposure. Next to the target names, the symbol * denotes that the ChemCam target was imaged by the MAHLI, the symbol ** denotes that the dust removal tool was used before the MAHLI image was taken, and ~ signifies that a location close to the ChemCam target was imaged by the MAHLI.</p> <p><em>Table S4</em>. The mean, median, minimum and maximum G<sub>MEAN</sub> and the minimum and maximum grain size regime (GSR) for each locality in the Murray formation.</p>
Fig. 4 in Kidney anatomy, histology and histometric traits associated to renosomatic index in Gymnotus inaequilabiatus (Gymnotiformes: Gymnotidae)
Fig. 4. Histological cross-sections of the head and exocrine kidney demonstrating different granulomatous structures in Gymnotus inaequilabiatus. a. severe aggregation of MMCs outer to granuloma in the exocrine kidney; PAS, bar scale = 20 µm. b. a clump of melanogenic macrophages (dark pigmented cells) adjacent to granuloma in the head kidney. The hematopoietic tissue is edematous and atypical. Some rodlet cells (black arrow) are observed. Granuloma presents a compact and thick layer of collagen with internal necrotic content surrounded by epithelioid cells (white arrows); H&E, bar scale = 10 µm. c. two well-defined granulomas with substantial internal necrotic content involved by fibrous tissue. A slight layer of MMCs aggregates close to the external wall of granuloma. TM, bar scale = 10 µm. d. MMCs aggregates both internally and externally to granuloma in the exocrine kidney. HE, bar scale = 10 µm.
Fig. 2 in Kidney anatomy, histology and histometric traits associated to renosomatic index in Gymnotus inaequilabiatus (Gymnotiformes: Gymnotidae)
Fig. 2. Cross-section of the head and exocrine kidney in Gymnotus inaequilabiatus. a. a transitional area between head (HE) and exocrine kidney (EX) drained by postcardinal vein (PCV). Lymphohematopoietic tissue is abundant in the head portion. MMCs are diffusely distributed in both portions. A thick fibrous capsule covers the organ (white arrow); HE, bar scale = 500 µm. b. the general aspect of the head kidney. Vascular sinusoids (white arrows) surrounding the lymphohematopoietic tissue enclosing the MMCs (black arrow); HE, bar scale = 200 µm. c. interstitial lymphohematopoietic tissue with MMCs deposits characterizes the exocrine kidney, in addition, the contoured tubules; renal corpuscle (white arrow); HE, bar scale = 200 µm. d. the exocrine kidney with a proximal convoluted tubule showing hyaline degeneration of the tubular epithelium often found in this species; HE, bar scale = 100 µm. e. exocrine kidney showing the corpuscle of Stannius (*). This structure is not lobulated, and is delimited by a fibrous capsule, and situated at the junction between head and exocrine portions; HE, bar scale = 500 µm. f. detail of junction between lymphohematopoietic tissue and corpuscle of Stannius in the head kidney. Fiber bundles subdivide both structures. Rodlet cells (white arrow), macrophages (M) and eosinophilic granulocytic cells (black arrow); granulocytic (G) and secretory cells (SC) internally fill the corpuscle; HE, bar scale = 50 µm.
Fig. 3 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 3. Monthly variation of Cyphocharax voga GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Fig. 5 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 5. Monthly variation of Oligosarcus jenynsii GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Fig. 2 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 2. Monthly variation of Astyanax fasciatus GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Reference dataset to check the Python package for the calculation of the OLR-based MJO index (OMI)
<p>The Python package (<a href="https://doi.org/10.5281/zenodo.3613752">10.5281/zenodo.3613752</a>) for the calculation of the OLR-based MJO (OMI) index comes with integration tests, with which the users can check the calculation results.</p> <p>However, in order to run some of these tests, input and reference datasets are needed. Specifically, a dataset of Outgoing Longwave Radiation (OLR) described by Liebmann and Smith (1996) is needed as the input and OMI values described by Kiladis et al. (2014) are needed as the reference.</p> <p>These files are provided by this upload and can be downloaded either as .tar.gz or as .zip file.</p> <p>Whereas exactly the files provided here are needed for the tests, updated versions of these datasets can be found on the websites of NOAA: <a href="https://psl.noaa.gov/data/gridded/data.interp_OLR.html">https://psl.noaa.gov/data/gridded/data.interp_OLR.html</a> and <a href="https://www.esrl.noaa.gov/psd/mjo/mjoindex/">https://www.esrl.noaa.gov/psd/mjo/mjoindex/</a>.</p>
Fig. 2. Female Femoral Tooth index. A in Ichneumonid wasps from Madagascar. VI. The genus Pristomerus (Hymenoptera: Ichneumonidae: Cremastinae)
Fig. 2. Female Femoral Tooth index. A. Tooth absent (FFT = 0). B. Tooth distinct, but wider than high (FFT = 1). C. Tooth higher than wide (FFT = 2).
MESINESP: Medical Semantic Indexing in Spanish - Train dataset
<p><em><strong>Please use the <a href="https://doi.org/10.5281/zenodo.4612274">MESINESP2 corpus (the second edition of the shared-task)</a> since it has a higher level of curation, quality and is organized by document type (scientific articles, patents and clinical trials).</strong></em></p> <p> </p> <p> </p> <p><strong>INTRODUCTION</strong>:</p> <p>The Mesinesp (Spanish BioASQ track, see https://temu.bsc.es/mesinesp) training set has a total of 369,368 records. </p> <p>The training dataset contains all records from LILACS and IBECS databases at the Virtual Health Library (VHL) with a non-empty abstract written in Spanish. The URL used to retrieve records is as follows:<br> http://pesquisa.bvsalud.org/portal/?output=xml&lang=es&sort=YEAR_DESC&format=abstract&filter[db][]=LILACS&filter[db][]=IBECS&q=&index=tw&</p> <p>We have filtered out empty abstracts and non-Spanish abstracts. </p> <p>The training dataset was crawled on 10/22/2019. This means that the data is a snapshot of that moment and that may change over time. In fact, it is very likely that the data will undergo minor changes as the different databases that make up LILACS and IBECS may add or modify the indexes.</p> <p> </p> <p><strong>ZIP STRUCTURE:</strong></p> <p>The training data sets contain 369,368 records from 26,609 different journals. Two different data sets are distributed as described below:</p> <p> - <em>Original Train set</em> with 369,368 records that also include the qualifiers, as retrieved from VHL. <br> - <em>Pre-processed Train set</em><strong> </strong>with the 318,658 records with at least one DeCS code and with no qualifiers. </p> <p> </p> <p> </p> <p><strong>STATISTICS</strong>:</p> <p>Abstracts’ length (measured in characters)<br> Min: 12<br> Avg: 1140.41<br> Median: 1094<br> Max: 9428</p> <p>Number of DeCS codes per file<br> Min: 1<br> Avg: 8.12<br> Median: 7<br> Max: 53</p> <p> </p> <p> </p> <p><strong>CORPUS FORMAT</strong>:</p> <p>The training data sets are distributed as a JSON file with the following format:</p> <pre><code>{ "articles": [ { "id": "Id of the article", "title": "Title of the article", "abstractText": "Content of the abstract", "journal": "Name of the journal", "year": 2018, "db": "Name of the database", "decsCodes": [ "code1", "code2", "code3" ] } ] } </code></pre> <p>Note that the decsCodes field lists the DeCs Ids assigned to a record in the source data. Since the original XML data contain descriptors (no codes), we provide a DeCs conversion table (https://temu.bsc.es/mesinesp/wp-content/uploads/2019/12/DeCS.2019.v5.tsv.zip) with:</p> <p> - DeCs codes<br> - Preferred descriptor (the label used in the European DeCs 2019 set)<br> - List of synonyms (the descriptors and synonyms from both European and Latin Spanish DeCs 2019 data sets, separated by pipes)</p> <p> </p> <p>For more details on the Latin and European Spanish DeCs codes see: http://decs.bvs.br and http://decses.bvsalud.org/ respectively.</p> <p>Please, cite: Krallinger M, Krithara A, Nentidis A, Paliouras G, Villegas M. BioASQ at CLEF2020: Large-Scale Biomedical Semantic Indexing and Question Answering. InEuropean Conference on Information Retrieval 2020 Apr 14 (pp. 550-556). Springer, Cham.</p> <p> </p> <p>Copyright (c) 2020 Secretaría de Estado de Digitalización e Inteligencia Artificial</p>
Virulence mismatches in index hosts shape the outcomes of cross-species transmission
<p>Supplemental data and code for the paper <em>Virulence mismatches in index hosts shape the outcomes of cross-species transmission</em>.</p> <ul> <li>Dataset 1 is an R Shiny app allowing the estimation of rabies disease progression parameters for all observed combinations of virus source (reservoir) and recipient species, including within-species inoculations.</li> <li>Dataset 2 contains the original data and the analysis code used in this study.</li> </ul> <p>See the README files in each dataset folder for further information and usage instructions.</p>
Dorotheos Scholarios's Synoptic Index for Migne's Patrologia Graeca
<p>This data set contains the transcribed text of Dorotheos Scolarios Synoptic Index for Migne's Patrologia Graeca. The dataset is licensed under a <a href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</p> <p>A working web portal using this dataset can be found at :<a href="http://scholarios.graeca.org">http://scholarios.graeca.org</a></p>
Annual Snow Timing Index Rasters for the Western US and Alaska, WY2001-2019
<p>Here, a collection of rasters describing annual snow onset (SO), snow cover duration (SCD), and day of snow disappearance (DSD) for WY2001-2019 over Alaska, Canada, and the Western United States (boundary box: -152W, -100W, 32N, 68N) are available. Units are in calendar Day of Year (DOY) for SO and DSD, and in days for SCD. Filenames follow the convention, "index_west_threshold_spatialsubdomain.tif". For example, "SCD_west_5-0000005376-0000005376.tif" indicates the file contains snow cover duration raster data obtained using a 5% threshold. Spatial subdomain naming convention is described below.</p> <p>These data accompany a manuscript entitled, "Investigating the Relationship Between Peak Snow-Water Equivalent and Snow Timing Indices in the Western U.S. and Alaska". A diagnostic model of peak SWE as a function of remotely sensed snow timing indices (the dataset provided here) was developed in the course of this study to address the following questions: 1) Are peak SWE and snow timing related?; 2) How does this relationship vary across the western United States?; and 3) What meteorological and topographical conditions affect this relationship?</p> <p>These rasters were created in the Google Earth Engine (GEE) from the MODIS MOD10A1 v006 product (MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6). From the initial daily fSCA product, a moving median window (i.e., a low-pass filter) of filter length k=25 days was applied to obtain a binary snow cover series using fractional cover threshold of 1%, 5%, 10%, 20%, and 30% such that the timing indices may be extracted. The filter length smooths out small-scale short-lived snow deposition events that obscure snow timing. Pixels without seasonal snowpack (i.e., persistent year-round snow or little to no snow) were masked: within a given water year, pixels that 1) show no onset of snow between the 272nd day of year and end of calendar year (corresponding with the typical N. hemisphere timeframe for the start of snow accumulation), and/or 2) do not melt out between start of calendar year and the 272nd day of year (typical timeframe for the end of snowmelt) were masked. SCD was calculated as (DSD + 365 days - SO). Because of the large file size, rasters were split up spatially into multiple files by the GEE, and follow the naming convention for large file exports listed here: https://developers.google.com/earth-engine/guides/exporting. As stated, "the filename of each tile will be in the form baseFilename-yMin-xMin where xMin and yMin are the coordinates of each tile within the overall bounding box of the exported image." Each band represents a different water year and is labeled as such, e.g. "DSD_2001". </p>
Southeast US rainfall index for GRL paper "The Influence of a Resolved Gulf Stream on the Decadal Variability of Southeast US Rainfall"
<p>The data include Southeast US rainfall index based on GPCC monthly precipitation and 30 CMIP5 model historical simulations (first realization). Each rainfall dataset, observed or model simulated, has been linearly detrended and applied with a 5-year low-pass filter. The Southeast US rainfall index is calculated as the area averaged values of 5-year low-pass filtered rainfall over land regions bounded by 25°-38°N and 266°-284°E. The unit here is mm/day.</p>
Reproduction package for the paper "Mapping the spectral index of Cas A: evidence for flattening from radio to infrared"
<p>This is a basic reproduction package for the paper "Mapping the spectral index of Cas A: evidence for flattening from radio to infrared" by V. Domček et al. (2021). It provides raw, intermediate and final data sets, including figures and scripts to allow the reproduction of the work performed in this paper. It also lists software used and data archives containing the public observational data. </p> <p>An open access version of the paper can be found at https://arxiv.org/abs/2005.12677</p>
North Atlantic Oscillation (NAO) climate index hidden in ocean generated secondary microseisms
<p>Datatsets associated with "North Atlantic Oscillation (NAO) climate index hidden in ocean generated secondary microseisms". The data include the daily seismic cross-correlograms for station pairs located on land and at the seafloor offshore Ireland, 3D models used for the numerical simulations and the associated synthetic seismic data.</p>
A Daily Azores-Iceland North Atlantic Oscillation Index back to 1850
<p>A Daily resolution North Atlantic Oscillation Index from (01/01/1850) to (31/12/2014). The index is derived from the difference in atmospheric sea-level pressure values between the Azores and Iceland. The article describing the NAO index is currently under revision at Geoscience Data Journal.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.